公开(公告)号：US20180197547A1

公开(公告)日：2018-07-12

申请号：US15866079

申请日：2018-01-09

Applicant: Fujitsu Limited

Inventor： Ziqiang SHI ,  Liu LIU ,  Rujie LIU

IPC: G10L17/18 ,  G10L25/30 ,  G10L17/06 ,  G06F17/17

CPC classification number: G10L17/18 ,  G06F17/17 ,  G10L17/04 ,  G10L17/06 ,  G10L25/30

Abstract: An identity verification method and an identity verification apparatus based on a voiceprint are provided. The identity verification method based on a voiceprint includes: receiving an unknown voice; extracting a voiceprint of the unknown voice using a neural network-based voiceprint extractor which is obtained through pre-training; concatenating the extracted voiceprint with a pre-stored voiceprint to obtain a concatenated voiceprint; and performing judgment on the concatenated voiceprint using a pre-trained classification model, to verify whether the extracted voiceprint and the pre-stored voiceprint are from a same person. With the identity verification method and the identity verification apparatus, a holographic voiceprint of the speaker can be extracted from a short voice segment, such that the verification result is more robust.

公开(公告)号：US20140368689A1

公开(公告)日：2014-12-18

申请号：US14304324

申请日：2014-06-13

Applicant: FUJITSU LIMITED

Inventor： Qiong CAO ,  Rujie LIU

IPC: G06K9/62

CPC classification number: G06K9/6211 ,  G06K9/52

Abstract: An image similarity determining device and method and an image feature acquiring device and method are provided. The image similarity determining device comprises a preprocessing unit for extracting feature points of each input image region of an input image and each image region to be matched of a data source image; a matched feature point set determining unit for determining one to one matched feature point pairs between input image regions and image regions to be matched to determine matched feature point sets; a geometry similarity determining unit for determining a geometry similarity between the input image region and the image region to be matched based on distribution of respective feature points in the matched feature point sets; and an image similarity determining unit for determining similarity between input image and data source image based on geometry similarities between input image regions and corresponding image regions to be matched.

Abstract translation: 提供了图像相似性确定装置和方法以及图像特征获取装置和方法。 图像相似性确定装置包括：预处理单元，用于提取输入图像的每个输入图像区域的特征点和要与数据源图像匹配的每个图像区域; 匹配特征点集确定单元，用于确定输入图像区域和要匹配的图像区域之间的一对匹配的特征点对，以确定匹配的特征点集合; 几何相似度确定单元，用于基于匹配的特征点集合中的各个特征点的分布来确定输入图像区域和要匹配的图像区域之间的几何相似度; 以及图像相似性确定单元，用于基于输入图像区域和要匹配的对应图像区域之间的几何相似度来确定输入图像和数据源图像之间的相似性。

公开(公告)号：US20130230236A1

公开(公告)日：2013-09-05

申请号：US13854575

申请日：2013-04-01

Applicant: FUJITSU LIMITED

Inventor： Rujie LIU ,  Takayuki BABA ,  Susumu ENDO ,  Shuchi SHIITANI ,  Yusuke UEHARA ,  Daiki MASUMOTO ,  Shigemi NAGATA

IPC: G06F17/30

CPC classification number: G06F17/30247

Abstract: Embodiments describe an image retrieval apparatus. The image retrieval apparatus includes an unlabelled image selector for selecting one or more unlabelled image(s) from an image database; and a main learner for training in each feedback round of the image retrieval, estimating relevance of images in the image database and a user's intention, and determining retrieval results, wherein the main learner makes use of the unlabelled image(s) selected by the unlabelled image selector in the estimation. In addition, the image retrieval apparatus may also include an active selector for selecting, in each feedback round and according to estimation results of the main learner, one or more unlabelled image(s) from the image database for the user to label.

Abstract translation: 实施例描述了一种图像检索装置。 图像检索装置包括用于从图像数据库中选择一个或多个未标记图像的未标记图像选择器; 以及用于在图像检索的每个反馈回合中的训练的主要学习者，估计图像数据库中的图像的相关性和用户的意图，以及确定检索结果，其中主学习者利用未标记的未标记的图像 图像选择器在估计。 此外，图像检索装置还可以包括主动选择器，用于在每个反馈回合中并且根据主要学习者的估计结果，从图像数据库中选择一个或多个未标记的图像以供用户标记。

公开(公告)号：US20240346663A1

公开(公告)日：2024-10-17

申请号：US18613206

申请日：2024-03-22

Applicant: Fujitsu Limited

Inventor： Song GUO ,  Rujie LIU

IPC: G06T7/20 ,  G06V10/44 ,  G06V10/762 ,  G06V20/70

CPC classification number: G06T7/20 ,  G06V10/44 ,  G06V10/762 ,  G06V20/70 ,  G06V2201/07

Abstract: The present disclosure relates to a method, device and storage medium for improving multi-object tracking. According to an embodiment, the method comprises: performing a split operation on a tracklet provided for one object by a multi-object tracking model. The split operation comprises: determining an appearance feature sequence of the tracklet; determining a clustering label set of the appearance feature sequence; determining an image block label sequence; determining a fragment label sequence corresponding to continuous fragments, having the same clustering labels, in the image block label sequence; in a case where a length of the fragment label sequence is greater than the number of types of the clustering labels in the clustering label set, updating the image block label sequence and the fragment label sequence by performing an update operation; and splitting the tracklet based on the updated image block label sequence. The method may further comprise a merge operation.

公开(公告)号：US20240331378A1

公开(公告)日：2024-10-03

申请号：US18618134

申请日：2024-03-27

Applicant: Fujitsu Limited

Inventor： Ziqiang SHI ,  Liu LIU ,  Zhongling LIU ,  Rujie LIU

IPC: G06V20/40 ,  G06T7/12 ,  G06T7/13 ,  G06T7/246 ,  G06T7/277 ,  G06V10/26 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V20/41 ,  G06T7/12 ,  G06T7/13 ,  G06T7/248 ,  G06T7/277 ,  G06V10/26 ,  G06V10/44 ,  G06V10/751 ,  G06V20/49 ,  G06T2207/10016 ,  G06T2207/20132

Abstract: The embodiments of the present disclosure provide an apparatus for identifying items, a method for identifying items and an electronic device. The apparatus includes: a detector configured to detect one or more items in a reference area in one or more image frames in video data; a tracker configured to track an item detected in multiple image frames, wherein multi-hierarchy decision is performed on the item in the multiple image frames by using different time windows; and a classifier configured to identify the item according to a decision result of the tracker. Thereby, even if an item is moved briefly in some scenarios, the item will not be identified as two different items, which can reduce a situation in which the item is identified repeatedly and improve accuracy and robustness of item detection.

公开(公告)号：US20230281969A1

公开(公告)日：2023-09-07

申请号：US18096586

申请日：2023-01-13

Applicant: Fujitsu Limited

Inventor： Rujie LIU

IPC: G06V10/774 ,  G06V10/82 ,  G06V10/764 ,  G06V10/762

CPC classification number: G06V10/774 ,  G06V10/762 ,  G06V10/764 ,  G06V10/82

Abstract: A method of training a model, a device of training a model, and an information processing method is provided. The method of training a model comprises: determining a subsample set sequence composed of N subsample sets of a total training sample set; and iteratively training the model in sequence of N stages based on the subsample set sequence; wherein a stage training sample set of a y-th stage from a second stage to a N-th stage of the N stages comprises a y-th subsample set in the subsample set sequence and a downsampled pre-subsample set of a pre-subsample set composed of all subsample sets before the y-th subsample set; and each single class sample quantity of the downsampled pre-subsample set is close to or falls into a single class sample quantity distribution interval of the y-th subsample set.

公开(公告)号：US20220101040A1

公开(公告)日：2022-03-31

申请号：US17460316

申请日：2021-08-30

Applicant: FUJITSU LIMITED

Inventor： Meng ZHANG ,  Rujie LIU

IPC: G06K9/62 ,  G06K9/00

Abstract: A device and a method for classification using a pre-trained classification model and a computer readable storage medium are provided. The device is configured to extract, for each of multiple images in a target image group to be classified, a feature of the image using a feature extraction layer of the pre-trained classification model; calculate, for each of the multiple images, a contribution of the image to a classification result of the target image group using a contribution calculation layer of the pre-trained classification model; aggregate extracted features of the multiple images based on calculated contributions of the multiple images, to obtain an aggregated feature as a feature of the target image group; and classify the target image group based on the feature of the target image group.

公开(公告)号：US20210124915A1

公开(公告)日：2021-04-29

申请号：US17074663

申请日：2020-10-20

Applicant: FUJITSU LIMITED

Inventor： Fei LI ,  Jing YANG ,  Rujie LIU

IPC: G06K9/00 ,  G06T7/11 ,  G06T7/223 ,  G06T7/60 ,  G06T7/90

Abstract: A method and a device for detecting a hand action are provided. The method includes: identifying an area including hands of a person in one frame image of a video; dividing the area into multiple blocks and calculating a motion vector for each of the blocks; clustering multiple resulted motion vectors into a first cluster and a second cluster, wherein multiple first blocks corresponding to the first cluster of motion vectors correspond to one of a left hand and a right hand, and multiple second blocks corresponding to the second cluster of motion vectors correspond to the other one of the left hand and the right hand; identifying movements of the hands to which the first cluster and the second cluster correspond in a frame image subsequent to the one frame image; and matching the identified movements with a predetermined action mode to determine an action of the hands.

公开(公告)号：US20200302246A1

公开(公告)日：2020-09-24

申请号：US16744220

申请日：2020-01-16

Applicant: FUJITSU LIMITED

Inventor： Wei SHEN ,  Rujie LIU

IPC: G06K9/62 ,  G06N3/04

Abstract: An information processing method includes: inputting sample image into a machine learning architecture to obtain a first feature, and causing a first classifier to calculate a first classification loss; calculating a second feature based on the first feature and a predetermined first mask, and inputting the second feature into the first classifier to calculate an entropy loss; calculating a second mask based on the first mask and the entropy loss to maximize the entropy loss; obtaining an adversarial feature based on the first feature and the second mask, where the adversarial feature is complementary to the second feature; causing, by training the first classifier and the second classifier in association with each other, the second classifier to calculate a second classification loss based on the adversarial feature; and adjusting parameters of the machine learning architecture, the first classifier and the second classifier, to obtain a trained machine learning architecture.

公开(公告)号：US20140379730A1

公开(公告)日：2014-12-25

申请号：US14307687

申请日：2014-06-18

Applicant: Fujitsu Limited

Inventor： Xi LIU ,  Rujie LIU

IPC: G06F17/30

CPC classification number: G06F17/30663 ,  G06F17/30017 ,  G06F17/30247 ,  G06F17/30256 ,  G06F17/30259 ,  G06F17/30268 ,  G06F17/3028

Abstract: Embodiments provide a multimodality-based image tagging apparatus and a method for the same. The image tagging apparatus includes: a score generating unit configured to generate, for an inquiry image, multiple groups of first scores about all tags in an tagging dictionary by using a training image and multiple modalities of an image; a late-fusion unit configured to fuse the obtained multiple groups of scores to obtain final scores about all the tags; and a tag selecting unit configured to select one or more tag(s) with relatively large tag scores as tag(s) of the inquiry image according to the final scores about all the tags. With the embodiments, multiple modalities may be effectively fused, and a more robust and accurate image tagging result may be obtained.

Abstract translation: 实施例提供了一种基于多模态的图像标记装置及其方法。 图像标记装置包括：分数生成单元，被配置为通过使用训练图像和图像的多个模式，为查询图像生成关于标签词典中的所有标签的多组第一分数; 后融合单元，被配置为熔合所获得的多组分数以获得关于所有标签的最终分数; 以及标签选择单元，被配置为根据关于所有标签的最终分数，选择具有较大标签分数的一个或多个标签作为查询图像的标签。 利用实施例，可以有效地融合多种模态，并且可以获得更鲁棒和准确的图像标记结果。